Multimodality instrument for tissue characterization

ABSTRACT

A system with multimodality instrument for tissue identification includes a computer-controlled motor driven heuristic probe with a multisensory tip. For neurosurgical applications, the instrument is mounted on a stereotactic frame for the probe to penetrate the brain in a precisely controlled fashion. The resistance of the brain tissue being penetrated is continually monitored by a miniaturized strain gauge attached to the probe tip. Other modality sensors may be mounted near the probe tip to provide real-time tissue characterizations and the ability to detect the proximity of blood vessels, thus eliminating errors normally associated with registration of pre-operative scans, tissue swelling, elastic tissue deformation, human judgement, etc., and rendering surgical procedures safer, more accurate, and efficient. A neural network program adaptively learns the information on resistance and other characteristic features of normal brain tissue during the surgery and provides near real-time modeling. A fuzzy logic interface to the neural network program incorporates expert medical knowledge in the learning process. Identification of abnormal brain tissue is determined by the detection of change and comparison with previously learned models of abnormal brain tissues. The operation of the instrument is controlled through a user friendly graphical interface. Patient data is presented in a 3D stereographics display. Acoustic feedback of selected information may optionally be provided. Upon detection of the close proximity to blood vessels or abnormal brain tissue, the computer-controlled motor immediately stops probe penetration. The use of this system will make surgical procedures safer, more accurate, and more efficient. Other applications of this system include the detection, prognosis and treatment of breast cancer, prostate cancer, spinal diseases, and use in general exploratory surgery.

This application is a continuation of application(s) application Ser.No. 09/017,519 filed on Feb. 2, 1998 now U.S. Pat. No. 6,109,270application Ser. No. 08/795,272 filed on Feb. 4, 1997 now abandoned.

ORIGIN OF THE INVENTION

The invention described herein was made by employees of the UnitedStates Government and may be manufactured and used by or for theGovernment for governmental purposes without payment of any royaltiesthereon or therefor.

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

The present invention relates in general to the field of sensors andinstruments, and it particularly relates to medical diagnostic,prognostic, treatment and surgical instruments. This invention furtherrelates to a system which heuristically provides tissue identificationin neuroendoscopy and minimally invasive brain surgery.

2. Description of the Prior Art

Existing medical instruments provide general diagnoses for the detectionof tissue interface such as normal tissue, cancer tumor, etc. However,such detection has been limited clinically to tactile feedback,temperature monitoring, and the use of a miniature ultrasound probe fortissue differentiation during surgical operations. Stereotactic computedtomography (CT) scanners, magnetic resonance imaging (MRI) devices, andsimilar other instruments provide guided brain biopsy and preoperativescans for use. in neurosurgical surgeries. These scans allow samples ofbrain tissue to be obtained with some degree of accuracy.

However, existing devices provide diagnostic data of limited use,particularly in neurosurgery, where the needle used in the standardstereotactic CT or MRI guided brain biopsy provides no information aboutthe tissue being sampled. The tissue sampled depends entirely upon theaccuracy with which the localization provided by the preoperative CT orMRI scan is translated to the intracranial biopsy site. Any movement ofthe brain or the localization device (e.g., either a frame placed on thepatient's head, or fiducials/anatomical landmarks which are in turnrelated to the preoperative scan) results in an error in biopsylocalization. Also, no information about the tissue being traversed bythe needle (e.g., a blood vessel) is provided. Hemorrhage due to thebiopsy needle severing a blood vessel within the brain is the mostdevastating complication of stereotactic CT or MRI guided brain biopsy.

Several other drawbacks are associated with existing devices instereotactic CT or MRI guided brain biopsy. For instance, this procedureis labor intensive and requires the transfer of localization coordinatesfrom the preoperative scan to the localization device. The depth towhich the needle is passed within the brain is also subject to humanerror. No real-time information is gained about either the tissue beingbiopsied or the tissue being traversed en route to the biopsy site. Thebiopsy information is not provided on a real-time basis, and may take aday or more for various staining procedures to be performed by theneuropathologist on the sampled tissue. The non-simultaneity of thesampling, analysis and use precludes existing stereotactic CT and MRIguided brain biopsy from being performed remotely, such as in spacemissions, long term space exploration travels, or hospitals that are notstaffed with a neurosurgeon.

CT and MRI scans allow neurosurgeons to identify anatomical regions ofthe brain with an accuracy on the order of one or two millimeters. Aspresented later, these scans are not adequate for the preciselocalization needed by neurosurgeons to perform optimally safe surgery.

CT and MRI scans are obtained pre-operatively. In a conventionalstereotactic CT or MRI guided brain biopsy, a frame is applied to thepatient's head and the scan obtained. The coordinates of the desiredtargets on the scan are then translated to corresponding coordinates ofthe frame. The patient then undergoes the biopsy through a small holedrilled in the skull (three or four millimeters in diameter) using aplastic or metal biopsy “needle” that most commonly aspirates a verysmall core of tissue (on the order of one or two millimeters in diameterby three or four millimeters in length). Any movement of the brain, suchas can be due to changing the position of the patient from the positionin which the scan was obtained, can introduce error into the biopsycoordinates.

A much greater practical problem arises when the pre-operative scan isused to guide the removal of a tumor deep within the brain. As the tumoris removed, or the brain retracted to permit access to the tumor, thecoordinates from the pre-operative scans become somewhat invalid. Thiserror is especially troublesome with recently developed systems that usean optically-encoded “arm” in an electro-optical camera system forlocalization during neurosurgical operations.

Another significant problem with using CT and MRI scans for localizationis that they do not provide functional localization. As neurosurgicalprocedures become more precise, the need increases for knowledge of thefunctional organization of the brain. The localization necessary toperform pallidotomy procedures for Parkinson's disease is one examplewhere anatomical localization based on CT or MRI scanning is inadequatefor optimal treatment, since electrophysiological mappingintraoperatively is important to maximize the benefit of the operationfor a given patient.

There have been a few recent advances in preoperative scanning thatprovide some information about the functional organization of the brain.Functional MRI and PET (Positron Emission Tomography) are two examplesof such recent scanning techniques. However, these scanning techniquesare hampered either by their limited range of functions which can beutilized (e.g., functional MRI) or their relatively poor resolution, forexample on the order of one half to one centimeter (e.g., PET).

SUMMARY OF THE INVENTION

It is an object of the present invention to enable the placement ofmultiple neurosurgical sensors and/or effectors (or tools), such as abiopsy probe in any desired region of the brain with extreme accuracy.

Another object of the present invention is to enable the localization ofthe neurosurgical sensors and/or effectors based on the characteristicsof the local brain environment, taking into consideration the anatomicaland functional variability among human (and non-human) brains.

Still another object of the present invention is to perform minimallyinvasive surgery, for example the localized placement of the effectorand treatment with minimal disruption of normal brain functions. Animportant method for minimizing invasiveness is miniaturization.

Yet another object of the present invention is the automation of part ofsurgical procedures. This objective is realized by incorporating twodisciplines. The first discipline is robotics and remote control, andthe second discipline is neural net (or artificial intelligence)learning. Remote control has been used by NASA scientists in missionseither too dangerous or impossible for human performance, such assending an unmanned submarine beneath the Antarctic ice cap and arobotic rover into an Alaskan volcano crater. Neural net learning allowsa computer to gather information from repeated exposures to normal andabnormal brain tissue which can then be applied to a novel situation, inorder to decide the type of tissue being encountered.

A further object of the present invention is to provide a heuristicrobotic system with a multimodality instrument for tissueidentification. This instrument will replace “dumb” metal needles usedto perform exploratory surgeries such as biopsies. It will also helpavoid certain complications associated with the translation of thelesion (e.g., tumor) coordinates from MRI/CT scans to the actual lesionusing the inventive multimodality instrument. These complicationsinclude the inability to obtain tissue which will allow theneuropathologist to make a diagnosis, and the risk of severing a bloodvessel which may result in a hemorrhage causing significant neurologicalinjury or possibly death.

Briefly, the foregoing and other features and advantages of the presentinvention are realized by a robotics system with a multimodalityheuristic instrument for tissue identification. The instrument includesa computer-controlled motor driven probe with a multisensory tip, e.g.,a group of sensors may be selectively incorporated into the probe tip,or near the probe tip or as part of the probe.

In a preferred embodiment, the probe is driven by a computer-controlledactuator mechanism to the appropriate depth within the brain forobtaining a continuous and real time output of resistance or density ofthe tissue being penetrated. This output is received into a neural netlearning program which is constantly learning not only the differencesbetween normal brain tissue and abnormal brain tissue, such as tumors,but also the differences between various regions of the brain (e.g.,gray matter versus white matter).

In another embodiment where robotic insertion is not advantageous, theprobe can be a hand-held device and/or manually driven instead of motordriven.

The instrument further includes a micro laser-Doppler blood flow probehaving a diameter of less than approximately 1 mm. This probe detectsblood vessels before it can disrupt them, and it can further catalog theblood flow differences between either normal brain tissue, abnormalbrain tissue, or various regions of the brain such as gray matter andwhite matter (which are known to have a roughly fivefold difference inblood flow). A micro ultrasound probe, also less than approximately 1 mmin diameter, can aid in blood vessel detection and tissueidentification. A pO₂ (partial pressure of oxygen) microprobe, less than1 mm in diameter can aid in the detection of hypoxia which is anindication of turner malignancy.

Ion-selective micro electrodes can also be used to monitor suchimportant parameters as pH, calcium, sodium, potassium, and magnesium.Additionally, optical fluorescence and/or optical absorbance probes witha diameter of less than approximately 1 mm can also be used to monitoroxygen and carbon dioxide levels and other parameters of the signal. Thecombination of optical reflectance sensors and neural net learning tocharacterize the tissue being penetrated by the probe yields acharacteristic optical reflectance signature which is very valuable indistinguishing and identifying different tissues, such as blood vessels,tumors, grey matter and white matter.

The present multimodality instrument offers several advantages and canbe used in various commercial applications. For example, the presentinstrument improves the diagnostic accuracy and precision of generalsurgery, with near term emphasis on stereotactic brain biopsy. Itautomates tissue identification with emphasis on stereotactic brainbiopsy to permit remote control of the procedure. It also reducesmorbidity of stereotactic brain biopsy. The present instrument may alsobe used in conjunction with various surgical tools to increase thesafety, accuracy and efficiency of surgical procedures. For example, theuse of the multimodality instrument for monitoring patients with severehead injuries would greatly enhance the surgeon's capabilities inneurosurgery.

The present instrument may also be used in conjunction with endoscopesfor tissue identification in various types of surgery, and can beadapted to a hand held device and/or manually driven instead of motordriven for procedures where the automated robotic aspect is notadvantageous.

The present instrument may be used in a variety of applicationsincluding but not limited to tumor ablation in neurosurgery, generalexploratory surgery, prostate cancer surgery, breast cancer surgery,spinal surgery automated tissue identification for general surgery use(e.g., detecting the interface between normal tissue, cancer, tumor, orother lesion), automated stereotactic biopsy for neurosurgery,continuous monitoring for patients at risk for cerebral ischemia and/orincreased intracranial pressure (e.g., many patients withcerebrovascular disease, tumors, or severe head injury), and othersurgical procedures that could be performed in an automated/roboticfashion for minimizing trauma to the patient because of decreasedexposure time in comparison with procedures performed manually and/ormore invasively.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other features of the present invention and the manner ofattaining them will become apparent, and the invention itself will bebest understood, by reference to the following description and theaccompanying drawings, wherein:

FIG. 1 is a perspective schematic view of a robotic system configurationincorporating a multimodality instrument (shown schematically) accordingto the present invention;

FIG. 2 is an enlarged view of the instrument shown in FIG. 1;

FIG. 3 is a greatly enlarged view of a probe-cannula assembly comprisedof a multimodality probe and a cannula for use in the instrument ofFIGS. 1 and 2;

FIG. 4 is a schematic view of a monitor forming part of the roboticsystem of FIG. 1, illustrating an exemplary user interface graphicsdisplay forming part of a computer system;

FIGS. 5A and 5B represent a flow chart illustrating the general use ofthe robotic system of FIG. 1; and

FIG. 6 is a flow chart illustrating the learning process of theheuristic system of FIG. 1.

Similar numerals refer to similar elements in the drawing. It should beunderstood that the sizes of the different components in the drawingsare not in exact proportion, and are shown for visual clarity and forthe purpose of explanation.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 illustrates a robotics heuristic system 10 configured pursuant tothe present invention. The system 10 generally includes a stereotacticdevice 12 mounted on a subject's head 14; a robotics instrument 16;motor controller 18; and a computer system 20. While the system 10 willbe described in connection with a neurosurgical application, it shouldbe clear that the system 10 may be adapted for use in various othermedical and non medical applications.

The stereotactic device 12 is mounted on the subject's head 14 and isaffixed to the skull by means of retaining screws or pins 21. Thestereotactic device 12 further assists in locating a target site, forexample a brain tumor 19, by providing a fixed reference or fiducialcoordinate system. The stereotactic device 12 is well known in the fieldand is commercially available from Radionics, under the trade nameBRW/CRW stereotactic systems. In other applications the stereotacticdevice 12 may be replaced with another suitable fixation device, such asa “helmet” which conforms precisely to the subject's head 14, and/or adevice, such as an optical system that can be referenced to thepreoperative CT or MRI scan.

The robotic instrument 16 is mounted on the stereotactic device 12, andenables one or more sensors and/or one or more tools to be handled in aprecisely controlled fashion. In the present illustration for instance,a cannula 22 (within which a probe 24 is lodged) is designed toautomatically penetrate the subject's brain with an extremely highdegree of precision. In another embodiment, the probe-cannula assembly27 also shown in FIG. 3 and formed of the cannula 22 and the probe 24can be replaced with a probe-tool assembly wherein the tool is capableof performing various mechanical functions and medical treatment.

The robotic instrument 16 includes an actuator mechanism 26 capable ofdriving the sensors and/or tools with minimal damage to the braintissue. In the present illustration the actuator mechanism 26 includestwo stepper motors 28, 30 that automatically drive the probe 24 insidethe cannula 22, and that further drive the probe-cannula assembly 27into the brain tissue.

The actuator mechanism 26 is controlled by the motor controller 18 andthe computer system 20. The computer system 20 further includes a neuralnetwork program (comprised of a combination of neural networks) used toadaptively learn the information derived by the instrument 16, forinstance resistance and image features of normal brain tissue during thesurgery. Fast learning neural networks are used to provide nearreal-time modeling, and a fuzzy logic interface to the neural networkprogram is used to incorporate expert medical knowledge in the learningprocess. Identification of abnormal brain tissue is determined by thedetection of change and comparison with previously learned models ofabnormal brain tissues. Where the automated robotic aspect is notadvantageous the drive mechanism may be replaced with a manually-drivenmechanism or inserted directly by hand.

The components of the robotics heuristic system 10 will now be describedin greater detail in connection with FIGS. 2, 3 and 4. Starting with theinstrument 16, it is comprised of a mounting structure 70; two guiderails 72; a probe mounting plate 74; a cannula mounting plate 76; theactuator mechanism 26; the cannula 22; and the probe 24.

The mounting structure 70 generally includes a base 81 that removablyand adjustably mates with the stereotactic device 12 and provides amounting interface for the actuator mechanism 26. The base 81 may bemade of any suitable light weight material, such as aluminum, and mayassume various shapes that best suit the application for which it isused. The base 81 includes an opening 82 that serves as a guide for thecannula 22.

The two guide rails 72 serve as a guide mechanism, and extend from thebase 81 and serve as guides for the probe mounting plate 74, for it totranslate slidably along a desired direction with minimal or no pitch orroll deviation. The rails 72 may include markings 73 for providing avisual indication as to the position of the probe 24 relative to thebase 81. It is conceivable to replace the two rails 72 with anappropriate guide mechanism for the actuator mechanism 26. In anotherembodiment the guide mechanism allows the actuator mechanism 26 torotate around one rail 72 and to further translate linearly in one ormore predetermined direction.

The probe mounting plate 74 provides a means for securely holding themotor 28 and the probe 24. The probe mounting plate 74 includes twoadjacent openings through which the probe mounting plate 74 is allowedto journey slidably along the rails 72 for translation along thedirection of the arrow A—A In one exemplary illustration the directionof the arrow A—A coincides substantially with the vertical direction.One or more strain gauges 77 may be secured to the upper surface and/orlower surface of the probe mounting plate 74 to measure pressure oranother parameter acting on the cannula 22 or the probe 24.

As a safety feature, an adjustable mechanical stop 85 is mounted on thebase 81 to limit the amount of travel of the probe 24 in and through thecannula 22. For example, it is possible to initially limit the probeinsertion into the cannula 22 up but not exceeding the tip of thecannula 22. Subsequently, the mechanical stop 85 can be adjusted toallow the probe to extend beyond the cannula tip to another limit forthe purpose of deploying a probe effector.

The cannula mounting plate 76 provides a means for securely holding thecannula 22. The cannula mounting plate 76 includes an opening 83 throughwhich the cannula 22 is inserted for translation in the direction of thearrow B—B. In this exemplary illustration the direction of the arrow B—Bcoincides with that of the arrow A—A, though it is conceivable to designthe system 10 such that the probe 24 and the cannula 22 translate alongtwo different directions, at least before they mate.

The cannula mounting plate 76 serves as a retention guide to the cannula22 and is adjustably moveable relative to the base 81 along thedirection of the arrow B—B. One or more strain gauges 84 may be securedto the upper surface and/or lower surface of the cannula mounting plate76 to measure pressure or another parameter.

The cannula mounting plate 76 also serves as a safety mechanism forlimiting the travel of the probe-cannula assembly 27 beyond apredetermined level inside the brain. To this end, as the cannulamounting plate 76 reaches the base 81, or a predetermined distance abovethe base 81, it stops the advancement of the cannula 22 inside the braintissue. The distance between the cannula mounting plate 76 and the base81 may be adjusted even when the cannula mounting plate 76 has reached apredetermined position, by means of an adjustable mechanical stop 86provided for limiting the travel of the cannula mounting plate 76.

A position encoder 87 may be mounted on the probe mounting plate 74 toprovide information on the position of the probe 24 relative to areference mark on the base 81, or relative to markings 88 on a gradedruler 89. Similarly, a position encoder 90 may be mounted on the cannulamounting plate 76 to provide information on the position of the cannula22 relative to the reference mark on the base 81, or relative tomarkings 88 on the ruler 89.

The actuator mechanism 26 includes the two motors 28, 30 and theircorresponding lead screws 92 and 93, respectively. The motor 30 is astepper motor as is generally known in the field. In this particularillustration the motor 30 is available from Air Pax Corporation, inCalifornia, as model number L 9 2211-P2. The motor 28 is generallysimilar to the motor 30. It should however be clear that anothersuitable drive mechanism may alternatively be used to drive the cannula22 by itself or in combination with the probe 24.

The motor 30 is fixedly secured to the cannula mounting plate 76 via themotor housing, and is further secured to the base 81 by means of thelead screw 93. To this effect, one end 94 of the lead screw 93 isaffixed to the base 81, and the opposite end of the lead screw 93 isfree. The housing of the motor 30 traverses the lead screw 93. As themotor 30 runs, it causes its housing to translate linearly in thedirection of the arrow B—B, thus driving the cannula mounting plate 76and the cannula attached thereto.

The lead screw 92 extends through the housing of the motor 28 and theprobe mounting plate 74, and operates similarly to the lead screw 93.One end 95 of the lead screw 92 is affixed to the cannula mounting plate76, the housing of the motor 30, or to a guide 96 extending from, andsecured to the probe mounting plate 74. The opposite end of the leadscrew 92 is affixed to a top base plate 97. As the motor 28 runs, thehousing of motor 28 traverses the lead screw 92 to move linearly in thedirection of the arrow A—A, thus driving the probe mounting plate 74 andthe probe 24 attached thereto toward the cannula 22.

The cannula 22 is a hollow tubular member that is known in the field.The cannula 22 and the probe 4 are available from Chorus, located inMinnesota, as models 2120 and Archo PEN. The cannula 22 may includemarkings that provide the surgeon with a visual indication as to theinsertion progress of the probe-cannula assembly 27 within the braintissue. In another embodiment the cannula 22 may be replaced with asuitable guide mechanism or eliminated all together.

The probe 24 is a multimodality probe and is tightly secured to theprobe mounting plate 74. The probe 24 is connected to a power, signaland data cabling 98 that electrically and/or optically connects theinstrument 16 to the motor controller 18 and the computer system 20. Thecabling 98 is supported mechanically by any suitable support means (notshown) to prevent the cabling 90 from excessive bending.

As illustrated in FIG. 3, the probe 24 may include one or more of thefollowing sensors and/effectors (or tools) 99, although the following orother types of sensors and/or tools may alternatively be used dependingon the application for which they are used:

Strain gauge for measuring the penetration resistance. For example, thestrain gauge is available from Entran Devices Corporation, located inNew Jersey, as model number EPIH-111-100P/RTV.

Wick in needle microprobe for measuring interstitial pressure.

Laser Doppler blood flow sensor for measuring the proximity of the bloodvessels to the cannula tip as well as the rate of blood flow. Forexample, the laser Doppler blood flow sensor is available fromVASAMEDICS, located in Minnesota, as model number BPM².

Ultrasound probe for tissue identification.

Endoscope for providing image data. For example, the endoscope isavailable from Johnson & Johnson Professional, Inc., as model number83-1337.

pO₂ (partial pressure of oxygen) microprobe for measuring hypoxia.

Laser and/or other optical sensors for measuring the reflectanceproperties of tissues.

Temperature sensor to measure tissue temperature.

Ion specific sensors to measure the concentration of specific ions.

Microelectrode to measure brain electrical activity.

Tissue ablation laser.

Effectors such as: biopsy foreceps, malleable biopsy foreceps, graspingforeceps, micro-scissors, coagulator, irrigator.

The general use and operation of the system 10 will now be described inconnection with FIGS. 5A and 5B. The surgeon starts by positioning thestereotactatic device 12 on the subject's head 14. The stereotacticdevice 12 which is then mounted and tightly secured in place (block101). A CT or MRI scan can be obtained with the stereotactic device 12in place is used to relate the procedure to a prior CT or MRI scan. Ahole may be drilled in the subject's skull at a predetermined site,either manually or robotically using the system 10.

Having selected the proper sensors and/or tools forming part of theprobe 24, the surgeon mounts the Instrument 16 on the stereotacticdevice 12 (block 103) and calibrates the instrument 16, by checking thealignment of the probe 24 relative to the cannula 22 (block 105) andthen checking the proper functioning of the instrument 16, the motorcontroller 18 and the computer system 20 (block 107).

With the motor 30 in a non-operative mode and the cannula mounting plate76 stationed at a predetermined marking 88, the surgeon advances theprobe 24 toward the cannula 22 (block 109) by means of the motor 28,until the probe 24 is housed in its proper position within the cannula22. At which time the motor 28 is locked in position. In someembodiments of the system 10 it is desirable to have the tips of theprobe 24 and the cannula 22 flush with each other, while in otherembodiments, such as when tools are used, the tips of the probe 24 andthe cannula 22 are not flush. As an example, the tip of the probe 24 mayextend beyond the tip of the cannula 22.

Once the calibration stage is completed the surgeon starts the surgicalstage by instructing the computer system 20 to advance the probe-cannulaassembly 27 into the brain normal tissue (block 111) at a predeterminedcontrolled speed. The advancement of the probe-cannula assembly 27 isperformed by operating the motor 30, which causes the probe mountingplate 74, the motor 28, the cannula mounting plate 76, and theprobe-cannula assembly 27 to be driven simultaneously forward in thedirection of the arrow C.

As the probe-cannula assembly 27 is advancing into normal tissue theneural network program within the computer system 20 learns theproperties of the normal tissue (block 113) for further processing, aswill be described later. In certain applications it might be desirableto stop the advancement of the probe-cannula assembly temporarily untilsufficient data is collected or to provide the neural networks of thecomputer system 20 sufficient time to learn.

When either the surgeon or the computer system 20 determines thatsufficient data have. been collected, the actuator mechanism 26 isinstructed to advance the probe-cannula assembly to a predeterminedtarget site (115), for example tumor 19. The computer system 20continually checks to determine whether changes in the tissue propertiesor blood vessels have been detected (block 117). If the computer system20 does not detect property changes or blood vessels, it instructs theprobe-cannula assembly 27 to continue its travel toward the target site(block 115). If on the other hand the computer system 20 detectsproperty changes or blood vessels then it instructs the probe-cannulaassembly 27 to stop advancing (block 119).

Based on the detection result (block 117) the computer system 20notifies the surgeon of the appropriate action to be taken. As anexample, the computer system 20 determines whether it has detectedtissue property changes or blood vessels (block 121). If the computersystem 20 detects the proximity of blood vessels then the surgeon takesthe appropriate corrective measures, such as to stop the surgery or toreroute the probe-cannula assembly 27 (block 125). These correctivemeasures will enable the surgeon to avoid injury to the blood vessels.

If however, the computer system 20 detects tissue property changes(block 127), the neural networks compare the measured tissue propertiesand/or measured changes in tissue properties to previously learnedproperties and to reference properties (block 129). At this stage thesurgeon will confidently perform the necessary surgical procedure (block131).

A few exemplary surgical procedures that can be performed using thesystem 10 are:

Automated tissue identification for general surgery use, for detectingthe interface between normal tissue, cancer, or tumor. For example,surgery to remove prostate cancer can be accomplished accurately withminimal damage to normal tissue.

Automated stereotactic biopsy for neurosurgery.

Continuous monitoring for patients at risk for cerebral ischemia and/orincreased intracranial pressure.

With the development of multimodality effectors as well as multimodalitysensors on the neurosurgical probe, many neurosurgical procedures couldbe performed in an automated/robotic fashion, thus minimizing trauma tothe brain tissue because of the decreased exposure needed in comparisonto open procedures performed by a neurosurgeon manually. Examplesinclude the precise placement of (a) electrodes (epilepsy), (b)chemotherapeutic agents or radiation seeds (brain tumors), and (c)transplanted tissue (movement disorders such as Parkinson's disease).Increased precision of intraoperative localization and excision (orablation with a laser beam) of deep brain lesions would be possible.

In vivo injection of chemicals and tissue.

Scientific and animal research.

In one embodiment of the system 10, once the target site has beendetected and reached, the sensing probe 24 is retracted from the cannula22 by reversing the operation of the motor 28. A substitute probe, forinstance a probe 24 containing tools, can then be positioned inside thecannula 22 as described above, for aiding in the surgical procedure.

For neurosurgical biopsy applications, the instrument 16 is mounted onthe stereotactic frame 12 in order to have the biopsy probe 24 penetratethe brain in a precisely controlled fashion. The resistance of the braintissue being penetrated is monitored by a miniature (e.g., 0.050inch-diameter) circular strain gauge 93 attached to the tip of thebiopsy probe 24. Other modality sensors such as a miniature endoscope orlaser Doppler blood flow sensor are mounted near the probe tip toprovide real-time tissue images and the ability to detect the proximityof blood vessels.

The motor controller 18 drives, and precisely controls the motors 28,30. In a preferred embodiment the motor controller 18 includes a circuitboard that includes control logic for generating commands. The motorcontroller 18 is available from Motion Engineering, Inc., located inCalifornia, as model number PCX/DSP-800. The motor controller 18 furtherincludes an amplifier that generates the electrical current to drive themotors. The amplifier is available from Haydon Switch & Instrument,Inc., located in Connecticut, as part number 39105. Some or all of themotor controller 18 may be installed internally or externally relativeto the computer system 20.

With reference to FIG. 4, the computer system 20 generally includes aninstrument control unit 150, a central processing unit (CPU) 152, aneural network module 154, a fuzzy logic interface 156, and athree-dimensional (3D) graphics interface 158.

The instrument control unit 150 controls the various sensors and toolsand performs signal processing for the various sensors and tools of theprobe 24. As an example, the instrument control unit 150 can change thebrightness and contrast of images generated by an endoscope; change thesensitivity of a laser Doppler; switch laser sources; interpretreflectance signals; turns tools ON and OFF, etc.

The CPU 152 may have any suitable speed, for example 200 MHZ, foracquiring data, signal processing; controlling the graphics display; andproviding a user friendly interface. The computer system 20 may beconnected via a suitable communication link 157 to remote computers orother systems, which, for example enable the remote operation andcontrol of the system 10.

The neural network module 154 is used to adaptively learn theinformation provided by the instrument 16. As an example, the neuralnetwork module 154 can learn the characteristics of a particularsubject's normal brain tissue, such as resistance, color, size, shape,patterns, reflectance and other factors associated with the varioustypes of sensors and tools listed herein, while the surgery is beingperformed. Fast learning neural networks are used to provide nearreal-time modeling. The fuzzy logic interface 156 is added to the neuralnetworks to incorporate expert medical knowledge in the learningprocess.

Neural networks have described in several publications, for instance“How Neural Networks Learn from Experience”, by G. H. Hinton, ScientificAmerican, September 1992, pages 145-151. However, the combination ofvarious neural networks and the fuzzy logic interface 156 toautomatically conduct important aspects of complicated surgicalprocesses telemetrically, interactively with the surgeon, and withminimal risks to the patients is believed to be new.

The neural network module 154 will now be described in greater detail inconnection with FIG. 6 which illustrates the learning process 200 of theheuristic system 10. The neural network module 154 is trained (block202), In combination with the fuzzy logic, to create a model of varioustypes of tissues. The training is carried out using. one or acombination of suitable hybrid neural networks, including but notlimited to:

Backpropagation.

Radial basis function (RBF).

Infold self organizing feature map.

Cerebellar model articulation computer (CMAC).

For near real-time modeling of brain tissue, radial basis function(RBF), Infold self organizing feature maps and cerebellum modelarithmetic computer (CMAC) neural networks are used in variouscombinations to provide fast learning and enhanced modeling. Data usedfor learning include (1) instrument sensor data that has been signalprocessed to provide a set of parameters which captures the maincharacteristics of the tissue; (2) expert knowledge data that has beenprocessed through fuzzy logic to provide a set of parameters to aid inthe modeling of the tissue being penetrated; and (3) tissueidentification data provided by pre-trained neural networks to aid inthe classification of the tissue being penetrated.

Pre-trained neural networks are neural networks which have been trainedusing reference tissues and which are continually being updated based oninstrument sensor data obtained from surgery and confirmed tissue typefrom laboratory test results of the biopsied tissue.

As the probe-cannula assembly 27 advances through normal tissue (block111), the neural network module 154 analyzes the input signals (block204) from the instrument 16, and learns, on a near real-time basis(block 206), the specific properties of the normal tissue for theparticular subject. The neural network module 154 then develops anenvelope or model for the specific properties learned (block 208). Theneural network module 154 has the ability to develop a separate envelopefor each of the parameters or factors being sensed.

The neural network module 154 then places the envelope on top of thelearned model to define the normal range of the specific properties ofthe normal tissue, and to further identify the range of the propertiesof abnormal tissue. The neural network module 154 then compares theinput signals acquired by the instrument 16 to the envelope anddetermines whether the input signals fall within the envelope (block210). If the input signals fall within the normal tissue range definedby the envelope, the neural network module identifies the tissuepenetrated as normal tissue (block 212), and the computer system 20instructs the instrument to keep advancing the probe-cannula assembly 27toward the target site (block 115).

As the probe-cannula assembly 27 advances through the tissue the neuralnetwork module 154 continues learning on a near real-time basis andupdating the envelope. The foregoing routine (blocks 204, 206, 208, 210)is repeated for each of the envelopes (if more than one envelope havebeen developed) until the neural network module 154 determines that theinput signals fall outside one or a combination of envelopes of normalproperties.

Once such determination is made the neural network module 154 comparesthe input signals to the pre-taught training model and classifies thetissue type (block 214). For example, identification of abnormal braintissue is determined by detection of change and comparison withpreviously learned models of abnormal brain tissues. The computer system20 then inquires whether or not to stop the advancement of theprobe-cannula assembly 27 (block 216). If the surgeon determines thatfurther advancement is required then the routine of data collection,analysis and classification (blocks 204, 206, 208, 210, 214) iscontinued until such time as the surgeon instructs the computer system20 to stop the advancement of the probe-cannula assembly 27 (block 218).In certain applications it might be desirable to have the probe-cannulaassembly 27 penetrate the abnormal tissue (or tumor) completely andextend beyond it.

The operation of the multimodality system 10 is controlled through theuser friendly three-dimensional (3D) graphics interface 158. Real-timetissue identification information is also displayed graphically. Patientdata is presented in a three dimensional stereographics display 161.Acoustic feedback of selected information is provided as an aid to thesurgeon. Upon detection of the close proximity to blood vessels orabnormal brain tissue, the actuator mechanism 26 immediately stops theprobe penetration. The 3D stereographics display 161 is comprised ofthree orthogonal views of the anatomy, with each view presenting theappropriate sequence stack of MRI or CT scans. In each view, a graphicalmodel of the probe is driven in motion in real-time by data incomingfrom the probe. In addition, the multisensory outputs from the actualprobe are displayed graphically in real-time at the probe tip in eachview. A closeup of the probe tip is provided to show fine details of theMRI or CT scans as the probe approaches each layer. These views providea virtual reality environment for visualizing the approach to the targetsite and the probe proximity to critical arteries.

The 3D graphics interface 158 further includes an indicator 163 for therobotics system that provides an indication as to the status and trendanalysis of the system 10. The 3D graphics interface 158 may alsoprovide access to patient records or data, to remote surgery experts andto various databases.

In another embodiment for diagnosis or surgery where robotic insertionis not advantageous, the probe as described above can be a hand-helddevice inserted by hand into the subject.

While specific embodiments of the present system were illustrated anddescribed in accordance with the present invention, modifications andchanges of the system dimensions, use and operation will become apparentto those skilled in the art, without departing from the scope of theinvention.

What is claimed is:
 1. A method for characterizing tissue, the methodcomprising: penetrating a patient's body, adjacent to a selected tissue,with a probe, contained in a needle and having at least first and secondsensors incorporated therein that are configured to characterize thetissue, where the at least first sensor is drawn from the group ofsensors consisting of: a sensor of elastic resistance of a selectedportion of the tissue to mechanical deformation of the selected tissueportion; a wick in needle sensor of interstitial pressure associatedwith the tissue; a laser Doppler sensor of blood flow associated withthe tissue; an ultrasonic probe; an endoscope; a sensor ofpartial-pressure of oxygen associated with the tissue an optical sensorfor measuring at least one selected optical property of the tissue; asensor of a temperature associated with the tissue; an ion-specificsensor of at least one ion associated with the tissue; a microelectrodesensor for measuring at least one selected electrical propertyassociated with the tissue; a mechanical effector; and a tissue ablationlaser; and the second sensor is drawn from the group of sensorsconsisting of: a sensor of partial pressure of CO₂ associated with thetissue; a sensor of a material density associated with the tissue; afluorescence sensor for measuring fluorescence associated with thetissue; an absorbance sensor for measuring optical absorbance associatedwith the tissue; a chemical sensor of at least one chemical associatedwith the tissue; a position sensor for estimating present location ofthe needle within the patient's body; and a velocity sensor forestimating a velocity of the needle relative to a selected locationassociated with the patient's body; acquiring sensor signals from the atleast first and second sensors at a sequence of times as the needlepenetrates the patient's body; and analyzing the sensor signals acquiredby the at least first and second sensors using a computer systemincluding a neural network processing system that receives andadaptively analyzes information from said first and second sensors. 2.The method of claim 1, further comprising comparing informationassociated with at least one signal received from at least one of saidfirst and second sensors with corresponding information that would bereceived if said tissue were in a normal medical state.
 3. The method ofclaim 1, further comprising comparing information associated with atleast one signal received from at least one of said first and secondsensors with corresponding information that would be received if saidtissue were in at least one of a tumorous medical state and a cancerousmedical state.
 4. The method of claim 1, further comprising using saidultrasonic sensor to detect at least one of presence and absence ofblood vessels within said tissue and presence and absence of bloodvessels adjacent to said tissue.
 5. The method of claim 1, furthercomprising using said ion-specific sensor to measure concentration of atleast one of hydrogen ions, hydroxyl ions, calcium ions, sodium ions,potassium ions and magnesium ions present in said tissue.
 6. The methodof claim 1, further comprising selecting said tissue to be a selectedportion of said patient's brain.
 7. The method of claim 6, furthercomprising using said probe to detect presence of at least one ofcerebral ischemia and intercranial pressure in the selected portion ofthe brain.
 8. The method of claim 1, further comprising providing saidprobe with a capability to detect presence of an interface between afirst tissue that is normal and a second tissue that includes a tumorousor cancerous growth.
 9. The method of claim 1, further comprising usingsaid position sensor for estimating a penetration depth of said needleinto said patient's body.
 10. The method of claim 1, further comprisingusing at least one of said at least first and second sensors to measureblood flow in said tissue and to compare the measured blood flow with atleast one reference blood flow value that would be measured if saidtissue were in a normal medical state.
 11. The method of claim 1,further comprising using at least one of said at least first and secondsensors to measure blood flow in said tissue and to compare the measuredblood flow with at least one reference blood flow value that would bemeasured if said tissue were in at least one of a tumorous medical stateand a cancerous medical state.
 12. A medical device for identifying amedical condition, the device comprising: a needle capable ofpenetrating a patient's body, containing a multimodality probe andpositioned adjacent to a selected tissue, the probe including at leastfirst and second sensors incorporated therein that are configured tocharacterize the tissue, where the at least first sensor is drawn fromthe group of sensors consisting of: a sensor of elastic resistance of aselected portion of the tissue to mechanical deformation of the selectedtissue portion; a wick in needle sensor of interstitial pressureassociated with the tissue; a laser Doppler sensor of blood flowassociated with the tissue; an ultrasonic probe; an endoscope; a sensorof partial pressure of oxygen associated with the tissue; an opticalsensor for measuring at least one selected optical property of thetissue; a sensor of a temperature associated with the tissue; anion-specific sensor of at least one ion associated with the tissue; amicroelectrode sensor for measuring at least one selected electricalproperty associated with the tissue; a mechanical effector; and a tissueablation laser; and the at least second sensor is drawn from the groupof sensors consisting of: a sensor of partial pressure of CO₂ associatedwith the tissue; a sensor of a material density associated with thetissue: a fluorescence sensor for measuring fluorescence associated withthe tissue; an absorbance sensor for measuring optical absorbanceassociated with the tissue; a chemical sensor of at least one chemicalassociated with the tissue; a position sensor for estimating presentlocation of the needle within the patient's body; and a velocity sensorfor estimating a velocity of the needle relative to a selected locationassociated with the patient's body; a computer system, including aneural network processing system, programmed to acquire and adaptivelyanalyze sensor signals from the at least first and second sensors at asequence of times as the needle penetrates the patient's body and toanalyze the sensor signals acquired by the at least first and secondsensors to determine if at least one of a first medical condition and asecond medical condition is present.
 13. The system of claim 12, whereinsaid computer system is programmed to analyze said sensor signals bycomparing information associated with at least one signal received fromat least one of said first and second sensors with correspondinginformation that would be received if said tissue were in a normalmedical state.
 14. The system of claim 12, wherein said computer systemis programmed to analyze said sensor signals by comparing informationassociated with at least one signal received from at least one of saidfirst and second sensors with corresponding information that would bereceived if said tissue were in at least one of a tumorous medical stateand a cancerous medical state.
 15. The system of claim 12, wherein saidprobe uses said ultrasonic sensor to detect at least one of presence andabsence of blood vessels within said tissue and presence and absence ofblood vessels adjacent to said tissue.
 16. The system of claim 12,wherein said probe uses said ion-specific sensor to measureconcentration of at least one of hydrogen ions, hydroxyl ions, calciumions, sodium ions. potassium ions and magnesium ions present in saidtissue.
 17. The system of claim 12, wherein said tissue is selected tobe a selected portion of said patient's brain.
 18. The system of claim17, wherein said probe uses said probe to detect presence of at leastone of cerebral ischemia and intercranial pressure in the selectedportion of the brain.
 19. The system of claim 12, wherein said probe hasa capability to detect presence of an interface between a first tissuethat is normal and a second tissue that includes a tumorous or cancerousgrowth.
 20. The system of claim 12, wherein said probe uses saidposition sensor to estimate a penetration depth of said needle into saidpatient's body.
 21. The system of claim 12, wherein at least one of saidat least first and second sensors has a capability to measure blood flowin said tissue and to compare the measured blood flow with at least onereference blood flow value that would be measured if said tissue were ina normal medical state.
 22. The system of claim 12, wherein at least oneof said at least first and second sensors has a capability to measureblood flow in said tissue and to compare the measured blood flow with atleast one reference blood flow value that would be measured if saidtissue were in at least one of a tumorous medical state and a cancerousmedical state.